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      Scorzonera sensu lato (Asteraceae, Cichorieae) – taxonomic reassessment in the light of new molecular phylogenetic and carpological analyses

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          Abstract

          Abstract

          Scorzonera comprises 180–190 species and belongs to the subtribe Scorzonerinae . Its circumscription has long been the subject of debate and available molecular phylogenetic analyses affirmed the polyphyly of Scorzonera in its wide sense. We provide a re-evaluation of Scorzonera and other related genera, based on carpological (including anatomical) and extended molecular phylogenetic analyses. We present, for the first time, a comprehensive sampling, including Scorzonera in its widest sense and all other genera recognised in the Scorzonerinae . We conducted phylogenetic analyses using Maximum Parsimony, Maximum Likelihood and Bayesian analyses, based on sequences of the nuclear ribosomal ITS and of two plastid markers (partial rbcL and matK) and Maximum Parsimony for reconstructing the carpological character states at ancestral nodes. Achene characters, especially related to pericarp anatomy, such as general topography of the tissue types, disposition of the mechanical tissue and direction of its fibres, presence or absence of air cavities, provide, in certain cases, support for the phylogenetic lineages revealed. Confirming the polyphyly of Scorzonera , we propose a revised classification of the subtribe, accepting the genera Scorzonera (including four major clades: Scorzonera s. str., S. purpurea , S. albicaulis and Podospermum ), Gelasia , Lipschitzia gen. nov. (for the Scorzonera divaricata clade), Pseudopodospermum , Pterachaenia (also including Scorzonera codringtonii ), Ramaliella gen. nov. (for the S. polyclada clade) and Takhtajaniantha . A key to the revised genera and a characterisation of the genera and major clades are provided.

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          Most cited references 67

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          A DNA barcode for land plants.

            (2009)
          DNA barcoding involves sequencing a standard region of DNA as a tool for species identification. However, there has been no agreement on which region(s) should be used for barcoding land plants. To provide a community recommendation on a standard plant barcode, we have compared the performance of 7 leading candidate plastid DNA regions (atpF-atpH spacer, matK gene, rbcL gene, rpoB gene, rpoC1 gene, psbK-psbI spacer, and trnH-psbA spacer). Based on assessments of recoverability, sequence quality, and levels of species discrimination, we recommend the 2-locus combination of rbcL+matK as the plant barcode. This core 2-locus barcode will provide a universal framework for the routine use of DNA sequence data to identify specimens and contribute toward the discovery of overlooked species of land plants.
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            The Parsimony Ratchet, a New Method for Rapid Parsimony Analysis

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              Bayesian phylogenetic model selection using reversible jump Markov chain Monte Carlo.

              A common problem in molecular phylogenetics is choosing a model of DNA substitution that does a good job of explaining the DNA sequence alignment without introducing superfluous parameters. A number of methods have been used to choose among a small set of candidate substitution models, such as the likelihood ratio test, the Akaike Information Criterion (AIC), the Bayesian Information Criterion (BIC), and Bayes factors. Current implementations of any of these criteria suffer from the limitation that only a small set of models are examined, or that the test does not allow easy comparison of non-nested models. In this article, we expand the pool of candidate substitution models to include all possible time-reversible models. This set includes seven models that have already been described. We show how Bayes factors can be calculated for these models using reversible jump Markov chain Monte Carlo, and apply the method to 16 DNA sequence alignments. For each data set, we compare the model with the best Bayes factor to the best models chosen using AIC and BIC. We find that the best model under any of these criteria is not necessarily the most complicated one; models with an intermediate number of substitution types typically do best. Moreover, almost all of the models that are chosen as best do not constrain a transition rate to be the same as a transversion rate, suggesting that it is the transition/transversion rate bias that plays the largest role in determining which models are selected. Importantly, the reversible jump Markov chain Monte Carlo algorithm described here allows estimation of phylogeny (and other phylogenetic model parameters) to be performed while accounting for uncertainty in the model of DNA substitution.
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                Author and article information

                Contributors
                Journal
                PhytoKeys
                PhytoKeys
                3
                urn:lsid:arphahub.com:pub:F7FCE910-8E78-573F-9C77-7788555F8AAD
                PhytoKeys
                Pensoft Publishers
                1314-2011
                1314-2003
                2020
                08 January 2020
                : 137
                : 1-85
                Affiliations
                [1 ] Department of Higher Plants, Biological Faculty, Lomonosov Moscow State University, 119234, Moscow, Russia Lomonosov Moscow State University Moscow Russia
                [2 ] Botanischer Garten und Botanisches Museum Berlin, Freie Universität Berlin, Königin-Luise-Str. 6–8, 14195 Berlin, Germany Freie Universität Berlin Berlin Germany
                [3 ] I.M. Sechenov First Moscow State Medical University, Pharmaceutical Natural Science Department, Izmailovsky Boulevard, 8, 105043, Moscow, Russia I.M. Sechenov First Moscow State Medical University Moscow Russia
                Author notes
                Corresponding author: Norbert Kilian ( n.kilian@ 123456bgbm.org )

                Academic editor: A. Sennikov

                Article
                46544
                10.3897/phytokeys.137.46544
                6962254
                Maxim A. Zaika, Norbert Kilian, Katy Jones, Anastasiya A. Krinitsina, Maya V. Nilova, Anna S. Speranskaya, Alexander P. Sukhorukov

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                Categories
                Research Article
                Asteraceae
                Identification Key
                Molecular Systematics
                Phylogeny
                Taxonomy
                Asia
                Europe
                North Africa

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